GitHub
processing-images
Processes images with Sharp for optimization, resizing, format conversion, and batch operations. Use when optimizing web images, generating thumbnails, creating responsive image sets, or applying transformation...
doanchienthangdev AI Skills
GitHub ↗Explorez les skills IA publiés de doanchienthangdev et consultez leurs instructions source.
Statistiques de l’auteur
Skills indexés
128Étoiles des dépôts des skills indexés
384Forks du dépôt
128Moyenne des étoiles par skill indexé
3Les étoiles d’un dépôt peuvent se répéter entre ses skills.
Catégories populaires
Indexation récente
Explorer
GitHub
testing-with-playwright
Claude writes reliable E2E tests using Playwright for browser automation. Use when writing end-to-end tests, implementing Page Object Model, visual regression testing, API mocking, or cross-browser testing.
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optimizing-tokens
AI agent maximizes efficiency and minimizes costs through strategic token usage while maintaining output quality. Use when managing AI interactions, designing prompts, or reducing costs.
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designing-frontend-patterns
Claude designs scalable React component architectures using compound components, custom hooks, and state machines. Use when building reusable UI systems or complex component APIs.
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architecting-omega-systems
Designs scalable, resilient architectures using the 7 Omega principles. Use when building systems that need to scale to millions of users or designing platform-level infrastructure.
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ai-architecture
AI application architecture - gateway, orchestration, model routing, observability, deployment patterns. Use when designing AI systems, scaling applications, or building production infrastructure.
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security-hardening
Advanced security patterns including zero-trust architecture, secret management, CSP, and compliance frameworks
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building-react-apps
Builds production React applications with hooks, TypeScript, state management, and performance optimization. Use when creating React SPAs, component systems, or interactive UIs.
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implementing-defense-in-depth
AI agent designs layered security architecture with multiple independent protective barriers ensuring no single point of failure. Use when building security systems, reviewing architecture, or hardening applica...
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ml-serving-optimization
ML serving optimization techniques including batching, caching, model compilation, and latency reduction for production ML systems.
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building-express-apis
Builds production Express.js APIs with TypeScript, middleware patterns, authentication, and error handling. Use when creating Node.js backends, REST APIs, or Express applications.
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nextjs
Next.js development with App Router, Server Components, API routes, and full-stack patterns
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testingperformance-testing
Performance testing patterns including load testing, stress testing, benchmarking, and profiling for optimal application performance
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dataset-engineering
Building and processing datasets - data quality, curation, deduplication, synthesis, annotation, formatting. Use when creating training data, improving data quality, or generating synthetic data.
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user-feedback
Collecting and using user feedback - explicit/implicit signals, feedback analysis, improvement loops, A/B testing. Use when improving AI systems, understanding user satisfaction, or iterating on quality.
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chaos-engineering-and-resilience-testing
The agent implements chaos engineering practices for building resilient systems. Use when testing fault tolerance, designing game days, or validating system recovery.
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ml-workflow
ML development workflow covering experiment design, baseline establishment, iterative improvement, and experiment tracking best practices.
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requesting-code-reviews
AI agent requests effective code reviews through proper preparation, clear descriptions, and appropriate reviewer selection. Use when creating PRs, requesting feedback, or submitting for review.
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verifying-before-completion
AI agent validates work through evidence-based verification with comprehensive checklists, automated validation, and proof-of-work documentation. Use when completing tasks, preparing for review, or ensuring qua...
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ai-engineering
Building production AI applications with Foundation Models. Covers prompt engineering, RAG, agents, finetuning, evaluation, and deployment. Use when working with LLMs, building AI features, or architecting AI s...
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inference-optimization
Optimizing AI inference - quantization, speculative decoding, KV cache, batching, caching strategies. Use when reducing latency, lowering costs, or scaling AI serving.
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deployment-paradigms
ML deployment paradigms including batch vs real-time inference, online vs offline serving, edge deployment, and serverless ML.
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real-time-systems
WebSocket, Server-Sent Events, and real-time communication patterns for live features
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testing-omega-quality
Implements comprehensive testing across all quality dimensions - accuracy, performance, security, and accessibility. Use when building test strategies or ensuring production-grade quality assurance.
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.